code: def testShapesAndReconstructions(
      self, transform_name, target_channels
  ):
      # Transform the data, test shape
      transform = self.transform_pairs[transform_name][0]
      target_shape = tuple(
          [self.batch_size] + self.spec_shape + [target_channels]
      )
      with self.cached_session() as sess:
          spectra_np = sess.run(transform(self.audio))
      self.assertEqual(spectra_np.shape, target_shape)
  
      # Reconstruct the audio, test shape
      inv_transform = self.transform_pairs[transform_name][1]
      with self.cached_session() as sess:
          recon_np = sess.run(
              inv_transform(tf.convert_to_tensor(spectra_np))
          )
      self.assertEqual(
          recon_np.shape, (self.batch_size, self.audio_length, 1)
      )
  
      # Test reconstruction error
      # Mel compression adds differences so skip
      if transform_name != "melspecgrams":
          # Edges have known differences due to windowing
          edge = self.spec_shape[1] * 2
          diff = np.abs(
              self.audio_np[:, edge:-edge] - recon_np[:, edge:-edge]
          )
          rms = np.mean(diff**2.0) ** 0.5
          print(transform_name, "RMS:", rms)
          self.assertLessEqual(rms, 1e-5)
  
file_path: magenta/magenta/models/gansynth/lib/specgrams_helper_test.py
imports: import os
  from absl import flags
  from absl.testing import parameterized
  from magenta.models.gansynth.lib import specgrams_helper
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the SpecgramsHelperTest obj's underlying member method code with example usage: obj.testShapesAndReconstructions(transform_name, target_channels) without return types